Polymorphism in Python refers to the ability of different objects to respond to the same method or operator in different ways, depending on their data type or class. The term originates from the Greek words “poly” meaning many and “morph” meaning forms, indicating that a single interface can represent multiple underlying forms. In the context of programming and especially in Python, polymorphism plays a crucial role in writing flexible, reusable, and maintainable code. It allows functions, methods, and operators to behave differently based on the input objects, thereby supporting dynamic typing and late binding, which are core features of Python. In Data Structures and Algorithms Lab, polymorphism is particularly useful when implementing abstract data types, designing generic algorithms, and handling different data structures using a common interface. For instance, a sorting algorithm can work on lists of integers, floats, or even user-defined objects as long as those objects support comparison operations. This is achieved through polymorphic behavior, where the same operator or function adapts to the type of elements being processed. Python supports polymorphism in multiple ways, including method overloading (though limited), method overriding, duck typing, and operator overloading. Among these, operator overloading is a powerful feature that enables developers to define custom behaviors for standard operators such as +, -, *, ==, and others. This allows objects of user-defined classes to interact using familiar syntax, making code more intuitive and readable. Operator overloading in Python is implemented